Increasingly software is being sold and distributed on a subscription and usage bases as Software-as-a-Service (SaaS). SaaS products require an underlying support mechanism for providing statistical data gathering and aggregation for purposes of providing metrics related to a product's usage.
By and large, existing metering techniques store large amounts of usage metrics, some of which are duplicated in very large commercial databases. These existing techniques also lack the ability to track new and finer-grain metrics and lack the ability to recreate billing activities that extend for periods of time that extend back more than a few months. Additionally, the size and inflexibility of these existing metering techniques typically degrade processing throughput and user responsiveness to the very services that the users are paying for.
In the meantime, Internet Service Providers (ISPs) or service hosting sites are increasingly demanding the ability to provide more accurate, reproducible, and storage/processing efficient mechanisms for usage metrics based on metering. This is so, because the law recently changed permitting ISPs to charge consumers fees commensurate with their actual usage.
So, SaaS providers want the ability to track usage metrics in a more storage and processing efficient manner, and ISPs are demanding it so that they can charge heavy users fees more commensurate with their heavy usage. But, both the SaaS providers and the ISPs currently lack the underlying foundation to provide an acceptable solution.
Therefore, there is a need for improved service metering usage techniques.